1. Field of the Invention
The present invention relates to an image processing apparatus and an image processing method, and in particular to an image processing apparatus and an image processing method that can suppress noise in images.
2. Description of the Related Art
In recent years, image signals obtained from an image sensor contain more noise components due to a decrease in the size of pixels. A method is known for suppressing noise components contained in image signals by using multi-rate signal processing.
Japanese Patent Laid-Open No. 2008-293425 discloses a method in which image signals are separated into a plurality of frequency components using techniques such as the wavelet transform and the Laplacian pyramid, noise is suppressed for each frequency component, and then the frequency components are recomposited. For example, when the Laplacian pyramid is used, a low-band image is obtained by applying reduction processing to the original image, and a high-band image is obtained from a difference between an image obtained by enlarging the low-band image and the original image. By repeating reduction processing for a low-band image and generation of a high-band image from a difference from the original image, image signals are separated into frequency components layer-by-layer.
Frequency bands obtained in different layers are indicated by shaded areas in FIG. 6A; in this case, it is considered that there is no overlapping of bands. After noise is suppressed in each of these plurality of images containing frequency bands without any substantial overlapping, the images are recomposited. Recompositing can be realized by repeating compositing processing in which a reduced image is enlarged and added to a differential image in the next layer up.
As described above, processing for an image that was separated with no overlapping of frequency bands has the feature that, as recompositing processing is simple, compositing unevenness caused by recompositing is small. On the other hand, as all of the separated images are composited, noise that remains in the band-separated images even after noise suppression remains in the recomposited image. In particular, if high-frequency color noise, which is visually unpleasant, remains in the recomposited image, the color noise causes deterioration in the image quality of the recomposited image.
On the other hand, as disclosed in Japanese Patent Laid-Open No. 2009-199104, a method is known for applying frequency separation to an image such that frequency bands overlap. For example, when the Gaussian pyramid is used, a plurality of reduced images with different reduction ratios are generated from the original image. Frequency bands in the reduced images are indicated by shaded areas in FIG. 6B; in this case, the images partially overlap in terms of bands. Furthermore, when the Gaussian pyramid is used, every reduced image contains DC components. A recomposited image is obtained by applying noise suppression processing to each reduced image and compositing the reduced images using a compositing ratio calculated based on extracted edge signals.
The method disclosed in Japanese Patent Laid-Open No. 2009-199104 has the problem that a reduction in the detection accuracy for edge signals leads to the occurrence of compositing unevenness in edge portions of the recomposited image. On the other hand, this method has the advantage that, by adjusting the compositing ratio, the amount of noise can be controlled relatively easily; for example, high-band color noise and the like can be effectively reduced by using a large number of low-band images for flat image sections.
As described above, according to the method in which an image is separated into a plurality of bands with no overlapping by using the Laplacian pyramid and the like, noise is suppressed in each separated image, and then the separated images are recomposited, compositing unevenness does not easily occur as the compositing ratio is not calculated, but the noise suppression effect is difficult to improve because images of all bands are recomposited. On the other hand, according to the method in which an input image is separated into a plurality of images with overlapping frequency bands by using the Gaussian pyramid and the like, noise is suppressed in each separated image, and the separated images are composited in accordance with a compositing ratio calculated using edge signals and the like, the amount of noise can be controlled, but the accuracy of the compositing ratio influences the image quality.